Md Morshed Alam

Ph.D. in Computing and Information Systems, University of North Carolina at Charlotte, (2024)

Expertise

Research Interests

Critical Infrastructure Security, IoT Security, Cyber Physical Systems, AI Security, Connected Vehicle Security, Deep Reinforcement Learning

Articles

Alam, M. and Wang, W. (2021). A comprehensive survey on data provenance: State-of-the-art approaches and their deployments for IoT security enforcement. J. Comput. Secur. 29 (4) , pp. 423–446.

Conference Proceeding

Alam, M., Das, L., Roy, S., Shetty, S. and Wang, W. (2025). RESTRAIN: Reinforcement Learning-Based Secure Framework for Trigger-Action IoT Environment (pp. 562-567) Dubai: 2025 International Wireless Communications and Mobile Computing (IWCMC).

Wang, W., Alam, M. and Wang, Y. Privacy-Preserved and Incentivized Knowledge Sharing for Reinforced-Learning based IoT Platform Security Tokyo: 2025 8th Artificial Intelligence and Cloud Computing Conference (AICCC 2025).

Alam, M., Mohaimenur Rahman, A B M and Wang, W. (2024). IoTHaven: An Online Defense System to Mitigate Remote Injection Attacks in Trigger-action IoT Platforms 2024 IEEE 30th International Symposium on Local and Metropolitan Area Networks (LANMAN) (pp. 15-20).

Alam, M., Jahan, I. and Wang, W. (2024). IoTWarden: A Deep Reinforcement Learning Based Real-Time Defense System to Mitigate Trigger-Action IoT Attacks 2024 IEEE Wireless Communications and Networking Conference (WCNC) (pp. 1-6).

Alam, M., Sajid, M. Sajidul Islam., Wang, W. and Wei, J. (2022). IoTMonitor: A Hidden Markov Model-based Security System to Identify Crucial Attack Nodes in Trigger-action IoT Platforms 2022 IEEE Wireless Communications and Networking Conference (WCNC) (pp. 1695-1700).

• 2024: AI Teaching Fellowship, Old Dominion University